Lean AI

Preface

Launching and growing a new startup has always been a challenging endeavor. It requires most entrepreneurs and leaders to be open to trying new and innovative approaches to increase the odds of success—and that involves risk.

You can increase your chances for success by simply taking a rational and methodical approach to finding the best strategy for running the business. The Lean Startup movement has been one of the most successful systematic approaches to date. It has been widely adopted across the globe, changing the way startups are built and new products are launched.

The best growth teams in the world use the same approach to iterative learning by continuously running experiments for customer acquisition. They take the same logical approach to testing and tweaking their efforts to make the business grow as fast as possible.

Today, artificial intelligence, sensors, and digital platforms have created enormous opportunity for learning faster than ever before. Competing on the rate of learning will become the key difference between the startups that succeed and those that fail. Companies that embrace Lean AI will be able to test, learn, and iterate radically faster, raising the competitive bar for learning. By taking the wisdom outlined by Eric Ries in The Lean Startup into the golden dawn of artificial intelligence, we can radically improve our chances of successful outcomes.

This book provides practical advice on how you can scale up growth significantly faster when your company combines a Lean, nimble team with the judicious use of artificial intelligence and automation. It provides a pragmatic road map for growth in the age of intelligent machines. It’s an essential, modern guide any business can use to better understand how to measure and manage marketing in the era of big data. I wrote this book based on my personal experience on what it takes to build and leverage an “intelligent machine” to turbocharge your business growth and outsmart your competitors.

Who This Book Is For

This book is for any business entrepreneur, leader, executive, or investor who wants the competitive edge to scale up their customer acquisition growth better, smarter, and faster than the incumbents. Likewise, aspiring or experienced founders, CEOs, marketing executives, venture capitalists, and heads of growth and user acquisition, as well as key members on their teams, will benefit from reading it.

How This Book Is Organized

The book consists of six parts:

• Part I focuses on growth marketing with an overview of the current startup landscape and the biggest challenges currently facing new companies around customer acquisition. It provides an overview of the main components of Lean AI and takes a look at industry trends for leveraging AI for smart marketing.

• Part II looks at Customer Acquisition 3.0, providing you an overview of how to effectively leverage your customer data using “intelligent machines” powered by artificial intelligence. The chapters in this part explain how to identify tasks to automate, offer an overview of the intelligent machine framework, and provide information that will help you decide whether to build it or buy it based on your resource constraints.

• Part III provides guidance on how to select the right metrics for success that align on driving long-term growth. It explores the importance of creative assets and the area of cross-channel attribution to help optimize your intelligent machine.

• Part IV outlines five proven keys to user acquisition strategies and how to choose the right one for your business. It also dives deep into the “growth stack”—a set of tools that all work together to help you get the specific results you’re looking for, given your situation.

• Part V explores how to manage increased complexity and risk with the data needed for artificial intelligence to work. It also examines how the future growth team would coexist with humans and machines working together in ways that take advantage of the intelligent machine framework we share in the book.

• Part VI moves into how humans and machines can work symbiotically to produce the best work. We’ll take a look at that “next frontier,” including its potential for triumphs and the challenges it presents to your growth efforts.

Acknowledgments

I owe a tremendous debt of gratitude to the many people who have made this book possible.

First, I’m grateful to my amazing wife, Sophia Daryanani-Patel. She is my best friend, biggest cheerleader, and the love of my life. I really appreciate her giving me the time needed to focus on writing this book and being supportive throughout the process, as always with great insight, patience, and love.

This book took six months to write, but the concept for Lean AI took over two years to learn and perfect at IMVU. Kevin Henshaw was responsible for both recruiting me and always being my biggest advocate while supporting me with the resources needed to fully embrace Lean AI. I’m grateful to him and all the different people at IMVU who have always supported me in making Lean AI successful.

I thank Eric Ries for all his encouragement in helping to make this book idea come to life. His steadfast support for Lean AI from the start and belief in me in writing this book has been priceless. I couldn’t ask for a better mentor.

I’m grateful to the amazing people at O’Reilly Media for the extraordinary task of transforming the Lean AI story from an idea into this amazing book before you. Thank you to my editors, Melissa Duffield and Alicia Young, for seeing the vision through from the start, offering insightful editing, and expertly managing it throughout the entire process. Katie Tozer, Virginia Wilson, Monica Kamsvaag, Karen Montgomery, Rebecca Demarest, Jasmine Kwityn, and others helped to make this book a reality. They are all extremely talented and I’m so lucky to have the opportunity to work with them in writing this book.

I’d also like to thank the co-founders of Nectar9, Inc.—Jim Calhoun, CEO, and Sal Arora, the company’s chief data scientist—for their continued support, dedication, and the contributions they’ve made to the development of this book. We’ve enjoyed a close partnership built on a shared vision for marketing automation in the age of intelligent machines, pushing the envelope of possibility. I hope that spirit comes through in the pages of this book.

Thanks to all of the following incredible experts and peers for their patience in crowd-editing Lean AI: Abril McCloud, Aemee Doherty, Akbar Lalani, Andy Carvell, Claus Enevoldsen, Dan Olsen, Donnie Kajikawa, Etienne Guebriant, Fausto Gortaire, Grant Lee, Jasper Radeke, Marjaneh Ravai, Naomi Pilosof Ionita, Rajeev Raman, and Sergey Grytsuk. Their insights and suggestions were extremely important in making this book what it is.

To my mother, Kusum Patel, who has guided me, loved me, and consoled me through it all: I love you more than words can say.

I have no doubt neglected to include some very important people, which is an oversight on my part. I hope you can forgive the oversight and accept my sincere thanks!

Finally, and most importantly, I’d like to thank you, the reader. That you spent your precious time and attention reading this book means the world to me. Feel free to contact me at LomitPatel.com/Contact if there are any questions or concerns I can help you with.